We performed a comparison between Apache Spark and AWS Lambda based on real PeerSpot user reviews.
Find out in this report how the two Compute Service solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI."Apache Spark provides a very high-quality implementation of distributed data processing."
"The product’s most valuable feature is the SQL tool. It enables us to create a database and publish it."
"This solution provides a clear and convenient syntax for our analytical tasks."
"Apache Spark can do large volume interactive data analysis."
"The main feature that we find valuable is that it is very fast."
"The scalability has been the most valuable aspect of the solution."
"The most crucial feature for us is the streaming capability. It serves as a fundamental aspect that allows us to exert control over our operations."
"Spark can handle small to huge data and is suitable for any size of company."
"The feature I found most valuable about Lambda is the fact that it's serverless."
"The utilization of containers is particularly beneficial in overcoming the size limitations imposed on Lambda functions which not only allows us to work around these constraints but also contributes to the improvement and maintenance of our code."
"This product is easy to use."
"The solution is highly scalable."
"The initial setup of AWS Lambda is very straightforward and quick."
"Provides a good, easy path from when you're using an AWS cluster."
"The ease and speed of developing the services using any available language is the most valuable feature."
"We have no issues with the technical support."
"We've had problems using a Python process to try to access something in a large volume of data. It crashes if somebody gives me the wrong code because it cannot handle a large volume of data."
"If you have a Spark session in the background, sometimes it's very hard to kill these sessions because of D allocation."
"We are building our own queries on Spark, and it can be improved in terms of query handling."
"The product could improve the user interface and make it easier for new users."
"At the initial stage, the product provides no container logs to check the activity."
"The solution needs to optimize shuffling between workers."
"Apache Spark could potentially improve in terms of user-friendliness, particularly for individuals with a SQL background. While it's suitable for those with programming knowledge, making it more accessible to those without extensive programming skills could be beneficial."
"The solution must improve its performance."
"The feature to attach external storage, such as an S3 or elastic storage, must be added to AWS Lambda. This is its area for improvement."
"If you're running a new application with a significant load, you need to be prepared for potential bottlenecks."
"I would like to see more integration with other platforms."
"Its price should be improved. Its pricing is on the higher side. I am not sure if it currently supports the Go language. If it doesn't support the Go language, they can introduce it."
"We don't have the inbuilt modules in AWS Lambda. If more modules were built into or integrated with AWS Lambda, that would help developers to code."
"I think that perhaps Lambda could explore its functionality more."
"They should work on the solution's stability and pricing."
"I want to see support for longer applications. I need the 15-minute time-out window to improve."
Apache Spark is ranked 5th in Compute Service with 60 reviews while AWS Lambda is ranked 1st in Compute Service with 70 reviews. Apache Spark is rated 8.4, while AWS Lambda is rated 8.6. The top reviewer of Apache Spark writes "Reliable, able to expand, and handle large amounts of data well". On the other hand, the top reviewer of AWS Lambda writes "An easily scalable solution with a variety of use cases and valuable event-based triggers". Apache Spark is most compared with Spring Boot, AWS Batch, Spark SQL, SAP HANA and Apache NiFi, whereas AWS Lambda is most compared with AWS Batch, Amazon EC2 Auto Scaling, Apache NiFi, AWS Fargate and Google Cloud Dataflow. See our AWS Lambda vs. Apache Spark report.
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